Design record
Translate the model into rows
One row per pen
| 1 |
1 |
______ |
______ |
____ |
6 |
| 1 |
2 |
______ |
______ |
____ |
6 |
| 1 |
3 |
______ |
______ |
____ |
6 |
| 1 |
4 |
______ |
______ |
____ |
6 |
Continue for all 16 pens using your realised order.
Table checks
Your design table should contain:
- 16 rows and 16 distinct pen identifiers
- four rows for every treatment combination
- one row for every combination within each room
- diet and housing repeated for pigs sharing a pen in an observation table
Why can an observation table contain 96 rows without providing 96 treatment replicates?
Build challenges
After the stress test, report-back and design table:
- save the original allocation and stress-test record
- draw one build-challenge card
- construct the specified design with the same kit
- diagnose its design properties
- repair it, or explain why the constraint prevents a complete design
A convincing layout still needs a defensible allocation procedure.
Parts inventories: 1, 2, 3, 4, 5, 6, 7, 8, 9.
Challenge report
For every additional design, report:
- What is balanced?
- What comparison occurs within a block?
- What was randomised?
- What is confounded or otherwise limited?
- How many independent pen replicates remain?
- What repair or conclusion is justified?
Rebuild only after the instructor checks your design table.
Four-factor challenge
| Diet |
Green tile: standard |
Red tile: high-fibre |
| Housing |
No blue plate: standard |
Blue plate: enriched |
| Feeding |
No orange plate: once daily |
Orange plate: twice daily |
| Lighting |
No yellow plate: standard |
Yellow plate: extended |
- Set the azure room plates aside for this new common-environment scenario.
- Use all 16 pens and include every treatment combination.
- Randomly allocate combinations to pens and record the allocation.
Replication check
For the four-factor build:
- How many pens receive each complete treatment combination?
- How many pens receive each individual factor level?
- Do the six pigs replicate their pen’s treatment allocation?
- What changes if one pen is lost?
- How could you obtain two pens per combination using the same kit?
Workshop synthesis
For the original two-factor experiment:
- Pens received the treatment combinations.
- Rooms formed complete blocks.
- Chance selected positions within rooms.
- Two factors produced four combinations.
- Four pens independently replicated each combination.
- Complications affected units, observations or measurements differently.
Exit questions
Answer individually about the original two-factor experiment:
- What is the experimental unit, and why?
- What is the block?
- How many pen replicates are there per combination?
- What scientific question does the interaction address?
- Would weekly weighing increase treatment replication?
Challenge 1 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 2 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 3 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 4 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 5 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 6 kit
The image shows the remaining model. Set the unused room and its contents aside.
Back to challenges
Challenge 7 kit
Reuse your group’s pieces. Put unlisted markers aside and follow the challenge sheet.
Back to challenges
Challenge 8 kit
Set four yellow plates and 24 pink bricks aside. The image shows the initial 12-pen build.
Back to challenges
Challenge 9 kit
Set all four azure plates aside. Use paper slips for random allocation.
Back to challenges
Sources
Ruxton, Graeme D., and Nick Colegrave. 2016. Experimental Design for the Life Sciences. 4th ed. Oxford: Oxford University Press.
- Chapter 7: randomisation
- Chapter 8: factorial designs
- Chapter 9: blocking and covariates
Publisher page